This paper proposes a novel image corner matching algorithm using the similarity of spatial texture aiming at addressing the low matching rate and long computational time of traditional image corner matching algorithms. First, the paper calculated the spatial distance matrix of the corners in the image objects. Second, it transformed the measure of the image corners into the measure of spatial texture amplitudes by calculating the rayleigh quotient of the spatial distance matrix in the LBP feature space. Finally, it matched the image corners between different images by comparing their corresponding rayleigh quotients. This paper carried out the corner matching between different images captured under different circumstances. The experimental results demonstrate that our proposed image feature matching algorithm is robust on the image transformation and produces higher matching rate with less computational time. Compared with the-stated-of-art corner matching algorithm, the computational time is decreased by 48ms and 2408ms when the calculated features numbers are low and high respectively.